Massachusetts Institute of Technology
Department of Electrical Engineering & Computer Science
6.041/6.431: Probabilistic Systems Analysis
(Fall 2010)
Recitation 10
October 12, 2010
• Question 1. The two parts of this question are about identities for a probabilistic model with
sample space Ω, events A and B, and discrete random variable X. Any time conditioning on an
event is indicated, the event has positive probability. An identity is true when it holds without
any additional restrictions; it is false when there is any counterexample.
1.1. Which one of the following statements is true?
(a) P(A ∩B)may be larger than P(A).
(b) The variance of X may be larger than the variance of 2X.
(c) If Ac ∩Bc = ∅, then P(A ∪B) = 1.
(d) If Ac ∩Bc = ∅, then P(A ∩B) = P(A)P(B).
(e) If P(A)> 1/2 and P(B)> 1/2, then P(A ∪B) = 1.
1.2. Which one of the following statements is true?
(a) If E[X] = 0, then P(X > 0) = P(X < 0).
(b) P(A) = P(A |B)+P(A |Bc)
(c) P(B |A)+P(B |Ac) = 1
(d) P(B |A)+P(Bc |Ac) = 1
(e) P(B |A)+P(Bc |A) = 1
• Question 2. Provide clear reasoning; partial credit is possible
Heather and Taylor play a game using independent tosses of an unfair coin. A head comes up
on any toss with probability p, where 0 <p< 1. The coin is tossed repeatedly until either the
second time head comes up, in which case Heather wins; or the second time tail comes up, in
which case Taylor wins. Note that a full game involves 2 or 3 tosses.
2.1. Consider a probabilistic model for the game in which the outcomes are the sequences of
heads and tails in a full game. Provide a list of the outcomes and their probabilities of
occurring.
2.2. What is the probability that Heather wins the game?
2.3. What is the conditional probability that Heather wins the game given that head comes up
on the first toss?
2.4. What is the conditional probability that head comes up on the first toss given that Heather
wins the game?
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